Evaluation of Online Grocery Platform Alternatives Using Fuzzy ZNumbers

Abstract

Bacground: Retail management has evolved into a new business model with the development of online shopping habits. There may be significant differences between onsite service and online service in terms of customer expectations. Introduction: In this study, companies providing online grocery services in Turkey are evaluated by examining the services they provide from the perspective of customers. Fuzzy Z numbers, which also add the reliability of linguistic assessments to the analysis, are used in order to better describe the uncertainty. Methods: Fuzzy Z-analytic hierarchy method (FZ-AHP) is used to weight the decision criteria, and fuzzy Z-Grey relational analysis (FZ-GRA) method is used to find the best online market company. Results: As a result of the analysis, it is revealed that the most important criteria for online grocery shopping are minimum order amount and brand diversity. The results are also compared with ordinary fuzzy methods. Conclusion: The comparison of the methods used in the study shows that although the ranks of the criteria and alternatives are the same, using fuzzy Z linguistic scale results in a wider interval for the weights and the scores of the alternatives, which could change the ordering, especially in cases where criterion weights or alternative scores are very close to each other.